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Titlebook: Intelligent Tutoring Systems; 17th International C Alexandra I. Cristea,Christos Troussas Conference proceedings 2021 Springer Nature Switz

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21#
發(fā)表于 2025-3-25 05:48:36 | 只看該作者
22#
發(fā)表于 2025-3-25 09:42:07 | 只看該作者
Conference proceedings 2021e 2021. Due to COVID-19 pandemic the conference was held virtually.. The 22 full papers, 22 short papers and 18 other papers presented in this volume were carefully reviewed and selected from 87 submissions.. Conforming to the current move of education, work and leisure online, the title of ITS 2021
23#
發(fā)表于 2025-3-25 14:41:50 | 只看該作者
24#
發(fā)表于 2025-3-25 17:53:33 | 只看該作者
CompPrehension - Model-Based Intelligent Tutoring System on Comprehension Levelting explanatory feedback and follow-up questions to stimulate the learners’ thinking. The architecture and workflow are shown. We demonstrate the process of interacting with the system in the Control Flow Statements domain. The advantages and limits of the developed system are discussed.
25#
發(fā)表于 2025-3-25 23:44:33 | 只看該作者
Learning Logical Reasoning : Improving the Student Model with a Data Driven Approachly 300 students who processed 48 reasoning activities. This data was used in the development a psychometric model, a key element for initializing the learner’s model and for validating and improve the structure of the initial Bayesian network built with experts.
26#
發(fā)表于 2025-3-26 02:38:33 | 只看該作者
Comparing Bayesian Knowledge Tracing Model Against Na?ve Mastery Model, students would have saved time with the BKT model. The savings varied among concepts. Overall, students would have saved a mean of 1.28 min and 1.23 problems per concept. We also found that BKT models were more effective at saving time and problems on harder concepts.
27#
發(fā)表于 2025-3-26 06:24:18 | 只看該作者
Integrating Knowledge in Collaborative Concept Mapping: Cases in an Online Class Settingtanding of the topic, while the other group engaging shallow cooperation failed to build mutual understanding. The result shows the effectiveness of collaborative concept mapping in grasping online collaborative learning.
28#
發(fā)表于 2025-3-26 11:45:16 | 只看該作者
Towards Semantic Comparison of Concept Maps for Structuring Learning Activitiesm which compares didactic characteristic of concept maps, we present an extension which exploits a semantic approach to catch the actual meaning of the concepts expressed in the nodes of the map. We also present experimental results.
29#
發(fā)表于 2025-3-26 14:27:41 | 只看該作者
An Evaluation of a Meaningful Discovery Learning Support System for Supporting E-book User in Pair Lr; after completing the task, they can compare their learner-generated relations with expert-generated relations. The learning perception of one hundred and forty-three participants are analyzed and discussed.
30#
發(fā)表于 2025-3-26 20:18:15 | 只看該作者
Conference proceedings 2021 was “Intelligent Tutoring Systems in an online world”. Its objective was to present academic and research achievements of computer and cognitive sciences, artificial intelligence, and, due to its recent emergence, specifically, deep learning in tutoring and education
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